JOURNAL ARTICLE

Rainfall Prediction using Data Mining Techniques: A Systematic Literature Review

Shabib AftabMunir AhmadNoureen HameedMuhammad SalmanIftikhar AliZahid Nawaz

Year: 2018 Journal:   International Journal of Advanced Computer Science and Applications Vol: 9 (5)   Publisher: Science and Information Organization

Abstract

Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in advance regarding: ongoing construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. Published papers from year 2013 to 2017 from renowned online search libraries are considered for this research. This review will serve the researchers to analyze the latest work on rainfall prediction with the focus on data mining techniques and also will provide a baseline for future directions and comparisons.

Keywords:
Computer science Data science Flood myth Data mining Focus (optics) Baseline (sea) Predictive modelling Machine learning

Metrics

52
Cited By
3.44
FWCI (Field Weighted Citation Impact)
41
Refs
0.92
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Hydrological Forecasting Using AI
Physical Sciences →  Environmental Science →  Environmental Engineering
Stock Market Forecasting Methods
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Data Stream Mining Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
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